Tuesday, 24 November 2009

CRU emails - some sleuthing required. Help!

I have been following up on this email conversation from back in 1999 regarding Barrie Pittock, an ex-CSIRO researcher and Mike Hulme at CRU. Barrie is keen to help the WWF, who paid the CRU $US142,000 to produce a range of pamphlets that were to be used at the Kyoto conference.

Examining the impact of this range of emissions on temperatures, sea level rise and precipitation, the CRU scientists, in consultation with WWF's global biodiversity experts, identify a number threats to ecosystems and species posed by global warming. These include:

Coral bleaching in Australia, Central America and the Philippines. Forest fires in the Amazon, Alaska, Canada and Russia. Flooding in the Pantanal (Brazil), the Everglades and the Chesapeake Bay. Drought in parts of China, southern Africa and Central and South America. Loss of wildfowl habitat in North Dakota and other parts of the Northern Great Plains, Canada and Europe. In Canada, the duration of the Arctic sea-ice melt season will be extended, while precipitation will increase by between 15 and 45 percent by the year 2080. Sea ice melt will reduce the habitat available to the polar bear and could lead to its extinction. Thawing permafrost and forest cover loss will threaten species like the woodland caribou and the grey wolf.

The press release quoted Mike Hulme as saying:

"Evidence for the warming of our planet over the last 200 years is now overwhelming," said Dr. Mike Hulme, senior CRU climatologist and lead author of the WWF-sponsored study.

"Increasingly we are seeing the unmistakable fingerprint of human influence on global climate. With no action to curb emissions, the climate on Earth over the next century could become warmer than any the human species has lived through."

Here's a graphic from the WWF pamphlet illustrating decreases in rainfall in the two worst case scenarios. Winter rainfall in Perth for instance is forecast to fall by 50% - perhaps this is why some alarmists claim Perth will run dry any day now.

However, it appears that the WWF chose Hulme because of a paper he had written for Nature not long before. At least I think I have the right paper - I have had to make some inferences from the statements made in the emails. In the foreward to that paper, he wrote:

We find that, for some regions, the impacts of human-induced climate change by 2050 will be undetectable relative to those due to natural multi-decadal climate variability. If misleading assessments of and inappropriate adaptation strategies to climate-change impacts are to be avoided, future studies should consider the impacts of natural multidecadal climate variability alongside those of human-induced climate change.

and

Third, and most important at the catchment and water management scale, the impacts of multidecadal climate variability may be greater than the impacts of climate change (Fig. 1). For this climate model and for these experiments, the impacts of climate change on mean runoff by 2050 are significantly greater than natural climate variability in northern and southern Europe, but are no different to those of natural climate variability across large parts of western and central Europe. Similar results were found using the value of the monthly runoff that was exceeded 90% of the time; this is a measure of low flow, calculated from the 30 individual years of simulated monthly runoff. This is because although the percentage impact of climate change on this extreme is greater than on the mean, the impact of multi-decadal natural climate variability on this measure is also greater. Different results may be obtained with other definitions of extreme behaviour; where an increase in mean precipitation is associated with a greater relative increase in precipitation intensity, for example, the ¯ood signal might expect to be strengthened.

and

First, in some sectors and for some regions human-induced climate change may not have as great an impact on natural resources as might multi-decadal natural climate variability. Comparing present resources only with those simulated under future climate change may exaggerate the importance of climate change by ignoring the impacts of natural variability on these time-scales: the estimated impacts may occur even in the absence of human-induced climate change. Second, the results suggest that in many areas it will be very difficult to detect the impact of climate change, even on a multi-decadal time scale; the different spatial patterns of climate change and climate-variability impact, suggest that detection is best undertaken by looking over a large geographic area. Third, adapting our management systems to withstand multi-decadal natural climate variability (adequately designed) may, in some sectors and for some regions, be a sufficient medium-term response to the prospect of climate change although elsewhere it may not. Last, the results do not suggest that we can ignore the possibility that climate change will affect our natural resource base; what they do show is that some impacts of natural climate variability may be as great as, or greater than, the estimated impacts of human-induced climate change. This study shows that it is possible, and suggests that it is important, to compare the impacts of climate change alongside those of natural multi-decadal climate variability in order both to assess the importance of climate change and to help in the development of appropriate adaptation strategies.

My problem is this - I do not have the skills to decipher the original paper in Nature and to compare it to the pamphlets in order to find what changes were made to suit the needs of the WWF for $142,000. Are you able to give it a go?

Remember, this is the line that Barrie Pittock was pushing on Hulme:

What you are doing is using a strict Type I error criterion when others (WWF?) might think a Type II error criterion is more suitable (the Precautionary Principle), and reasonable people (like me of course!?) think a criterion in between which measures risk of serious impacts is

what is needed for policymakers.

I would be very concerned if the material comes out under WWF auspices in a way that can be interpreted as saying that "even a greenie group like WWF" thinks large areas of the world will have negligible climate change. But that is where your 95% confidence limit leads.

What impact did moving from a Type I to a Type II error criterion have?

2 comments:

First comment - both together give error ...What impact did moving from a Type I to a Type II error criterion have?

BOAB, you need a good statistician to give you the answer. It’s a long time since I did any stats and when I did I must admit I didn’t like them too much - but for the heck of it I looked up my Introductory Mathematical Statistics by Kreyszig which used to be the standard university text (at least years ago). Here are some links to scanned images of the first 6 pages of Ch 13 that deal with the topic. One Two Three

Briefly statistics are used to test and disprove a null hypothesis (sometimes called the alternative hypothesis). This is because you cannot prove a positive (there are always exceptions) so you have to set up an algorithm that you then disprove. Once the null hypothesis is disproved, the hypothesis is then proved. And here comes the fun part - actually setting out what the particular hypothesis is to be. Once established we test the null hypothesis with a set of data (most likely temperature data). Let me guess that the null hypothesis would be something like this: The temperature data from xx sources over a certain time period would show no change (i.e., not warming) and then test for that by looking at the deviation of the individual results from the initial results (say some type of variance). Now if the variance was always different from the null hypothesis being tested - say a positive variance, then the null hypothesis would be disproved, ergo the temperatures are increasing. However, some of the results would be expected to be random (noise in the signal whatever) and so there needs to be a way of excluding these results from the overall analysis. So we then choose a level to allow for random noise (the percentage of data points allowed to fall outside the expected boundary for the null hypothesis to still be accepted - see fig 13.1.1) and my guess is that a 5% level would be used. (Error type II) When it come to a type II error it now gets more complicated as my understanding is that the Error type II is calculated from the sample size and the number of points discarded to allow the null hypothesis to be disproved. Actually it could be quite large. (I think I am right here but I am no statistician).

Just picture these poor fellows working with this data trying to get it to behave in a particular fashion to produce a predetermined result and the bloody data goes the other way! LOL There must have been many sleepless nights. Funnily enough having taken the trouble to think this through a little I have a better understanding of the manipulation that has been evident by the computer programmers remarks about their code in some of the other information . These people have completely emasculated the data so that in my opinion the whole lot would have to be pretty well worthless. And funnily enough in wondering where to from here, I used Google to search for satellite records global warming and up came the late John Daly’s web site Still Waiting for Greenhouse. And scrolling down the page there is an entry “The Satellite Record 1979-2006" where he comments, “The newest and best way to determine global temperature is to use satellites to measure the temperature of the lower atmosphere, giving the Earth a uniform global sweep, oceans included, with no cities to create a false warming bias.” He’s right of course. Any other temperature data has been so compromised as to be worthless and should be discarded. So we can forget about AGW (what about all the AGW jobs?).

But back to the statistics. As a suggestion how about asking for assistance for Numbers Watch man, John Brignell. From everything on his blog and given the importance of the material, who knows he may be willing to advise.